(Fast-Track proposals will be accepted.)
Number of anticipated awards: 2–3
Budget (total costs):
Phase I: $200,000 for 9 months;
Phase II: $1,000,000 for 2 years
It is strongly suggested that proposals adhere to the above budget amounts and project periods. Proposals with budgets exceeding the above amounts and project periods may not be funded.
The deadline for receipt of all contract proposals submitted in response to this solicitation has expired. It was: November 13, 2012 by 5 p.m. EST.
Wireless sensors, and mobile devices and applications are increasingly marketed for health monitoring or interventions in consumer and clinical settings for prevention or management of chronic disease. A rapidly expanding market segment of technologies are focused on objective measures of health related behaviors (e.g., physical activity, sleep, diet, medication adherence, etc.). These mobile health technologies offer the capability to collect tremendous volumes of high quality health data, with continuous monitoring or event recording functions, in near real time. The expanding use of behavioral monitoring technologies, applications and mobile messaging provides new opportunities within consumer health, clinical care, and research. However, meaningful interpretation of the high volume of data generated from monitoring technologies is a challenge for the patient, care team and the researcher. Further, health monitoring technologies are often criticized for lacking additional contextual data to facilitate their interpretation.
Added to data from sensors and monitoring technology, self-reported measures can provide invaluable psychosocial, contextual, and environmental health-related information. Patient-reported outcomes in physical, mental or social health domains include physical abilities, fatigue, pain, depression, and social interactions. The expanded use of smartphone technologies lends itself to private, convenient, real-time data collection of self-reported measures. However, development or optimization of cross-platform mobile applications and scalable, efficient, cloud-based server platforms for rapid and real-time self-reporting and monitoring of these measures is needed.
Real-time integration of objective and patient-reported data could improve understanding and clinical management of acute and time-varying symptoms such as fatigue, pain, or depression experienced by cancer and other chronic disease patients. The integrated collection of objective and self-reported data can stimulate innovation within clinical and research settings, including clinical trials, clinical care, case-management, interventions, surveillance, and epidemiologic studies. For example, temporal integration of medication monitoring technologies, such as smart pill cases and sensor-based activity and sleep data, with patient-reported measures of depression, fatigue, or pain could enhance pharmaceutical clinical trial results. However, efficient systems and platforms for the capture, storage, integration, visualization, and reporting of these data streams are extremely limited or non-existent.
This topic's short-term goal is the development of innovative, secure, privacy-compliant mobile applications and paired analytic systems to control the collection, transfer, integration, analysis and reporting of objective and self-reported health-related measures. Longer term goals include the integration of these data systems and layers in health care and research settings to support customized monitoring and feedback loops, alerts, or alarms for consumers, patients, or members of the health care team.
Responses to this topic are expected to address the development of efficient methods and platforms to:
The resulting platform's utility extends from consumer health to clinical care and research settings for behavioral monitoring and prevention or management of disease. This topic encourages development of innovative, secure, privacy compliant mobile applications and 2-way mobile messaging techniques to facilitate and control the collection and transport of temporal data inputs from behavioral health monitoring technologies, self-reported measures, and associated metadata. The data acquisition systems described above must be paired with efficient, scalable back-end systems for data importation, storage, integration, visualization, analyses, and output reporting. Data elements may include (but are not limited to) wireless physical activity or sleep sensors/monitors, physiologic sensors, adherence monitors, sensor-based measures of stress or fatigue, dietary intake measures, geospatial location tags or linkages, images, text based annotations, speech recording and recognition; and self-reports of behavioral, psychosocial, environmental, and contextual data.
An essential task for each proposal is the development of transparent and customizable analytic tools for temporal data integration, visualization, and summary reporting of individual or group level measures. Recommended short term targets for system outputs are to provide reports to patients/participants, clinicians/researchers, and health systems; with longer term targets to provide reports directly to electronic medical records and public health surveillance systems. Recommended reports are consistent with current health outcomes policy priorities and objectives in the Meaningful Use Matrix for electronic health records established by the Health Information Technology Policy Committee (see http://healthit.hhs.gov/portal/server.pt).